RMME/STAT Joint Colloquium
Effects Across Time to Modeling States of a System: A Dynamical Systems Perspective on Modeling Social Science Data
Dr. Pascale Deboeck
University of Utah
Friday, November 15, at 11 AM ET
https://tinyurl.com/rmme-Deboeck
Modeling of repeated observations across time generally falls into one of two categories. The first is modeling observations as they change across time; that is, as a function of time. The second is to model the observations as they relate to prior observations; many common models in the social sciences are represented in this second category, including auto-regressive models, cross-lagged panel models, and latent difference score models. A less-common approach in this latter category are differential equation models. These models express relations between the state of observations and how they are changing. These models offer the opportunity to imagine change relations that may be commonly overlooked when modeling repeated measures. This talk will introduce the application of differential equation modeling to intensive, longitudinal data. Specific examples will include estimating derivatives from noisy data and the possibility of testing novel models of intraindividual dynamics.
Loading...
Reload document 
Open in new tab